Biometric systems such as iris and facial recognition systems may capture an image of a feature of a person having unique characteristics (e.g., an iris or facial features) for various purposes, for example, to confirm the identity of the person based on the captured image. In the example of iris recognition, an original high-quality image of the iris of a person may be captured by an optical system and converted into an iris code which is stored in a database of iris codes associated with a group of people. Similarly, a facial recognition system may capture certain facial features. These features are extracted from various processing methods and compared to similar records of facial features stored in a database. These stored records may be user files that are associated with a respective user and may later be used for comparison to captured images.
In order to later confirm the identity of a user, an image of the user's iris or face is captured, the respective comparison file is generated (e.g., iris codes or facial codes), and the comparison data for the captured biometric features is compared to the user data. If the comparison file exhibits a significant level of similarity with a stored iris code (e.g., the Hamming distance between the captured and stored image is less than a threshold), it can be assumed that the feature being compared (e.g., iris or facial features) of the user is a match with the identity associated with the stored user file.
Iris and facial recognition systems may each perform differently depending upon the characteristics of an optical system that is acquiring the iris or facial images. In general, an iris recognition system may operate in a range that is relatively close to a user, having focal point in a range of a few centimeters to less than meter from the lens. Because of the resolution required to acquire a useful iris image, the depth of field for conventional systems may be minimal, e.g., only a few centimeters. Conventional iris recognitions systems thus require a user to be stationary at a certain distance from the lens system, which is difficult and time consuming in modern applications such as cell phones, laptop computers, or access systems. Some systems employ complex combinations of lenses, sensors, focus, and illumination systems to capture useful iris images for subjects who are not stationary. However, such systems are complicated, expensive, and bulky. Facial recognition generally operates within a range that is further from the lens in order to capture the combination of facial features that is necessary for facial recognition. Facial recognition is less accurate than iris recognition, and in ranges where fewer facial features are captured this accuracy is further compromised.